Non-recursive resampling digital fir filter structure for demodulating 3G cellular signals

ABSTRACT

A filter and processing sequence is described that efficiently combines and performs two or more tasks required to demodulate a composite 3G (third generation) wireless signal formed by a combination of wideband 3.84 MHz (Universal Mobile Telecommunications System, identified, as acronym “UMTS”, or Universal Mobile Telecommunications System Terrestrial Radio Access, identified as acronym “UTRA”) carriers and narrowband 1.2288 MHz CDMA-2000 carriers. The three tasks, applied to each spectral component of the 3G wireless signal and described in the order of a traditional filtering structure are: Spectral translation, Bandwidth Reduction, and Sample Rate Selection. These tasks are traditionally implemented in three distinct pieces of hardware or software modules.

BACKGROUND OF THE INVENTION

A filter and processing sequence is described that efficiently combinesand performs two or more tasks required to demodulate a composite 3G(third generation) wireless signal formed by a combination of wideband3.84 MHz (Universal Mobile Telecommunications System, hereinafterreferred to as “UMTS” or Universal Mobile Telecommunications SystemTerrestrial Radio Access, hereinafter referred to as “UTRA”) carriersand narrowband 1.2288 MHz CDMA-2000 carriers. The three tasks, appliedto each spectral component of the 3G wireless signal and described inthe order of a traditional filtering structure are: Spectraltranslation, Bandwidth Reduction, and Sample Rate Selection. These tasksare traditionally implemented in three distinct pieces of hardware orsoftware modules.

The spectrum processed by the receiver is shown in FIG. 1 while a blockdiagram of a traditional digital receiver that processes a signal withthis spectrum is shown in FIG. 2. Note that the center frequencies ofthe wide-band signals are at multiples of 5.0 MHz while the centerfrequencies of the narrowband signals are at multiples of 1.25 MHz. Thesample frequencies, shown in parenthesis and indicated on the blockdiagram, are typical and can be changed within wide limits and arepresented here for purpose of discussing a specific example. Particularimplementation efficiency is to be had when the sample rate is selectedto be a rational multiple of the spectral spacing between band centers.This condition makes the spectral down conversion particularly simple.Similarly, implementation efficiency is also to be had when the samplerate is selected to be a rational multiple of the desired output samplerate. This condition makes the alignment of time samples with signalepochs particularly simple. Neither condition is a requirement for theprocess described here, since an arbitrary rate interpolator can be usedto align the sampling clock with either timing or carrier sub systems.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 depicts a Suite of Possible 3G Signal Spectra Formed by VariousCombinations of UTRA bands and CDMA-2000 Bands.

FIG. 2 shows Conventional Channelizer to Partition 3G Signal Set WithVarious Combinations of UTRA bands and CDMA-2000 Bands.

FIG. 3 a depicts Traditional Order of Channel Selection and Processing.

FIG. 3 b depicts Reordered Channel Selection and Processing.

FIG. 3 c depicts Reordering Re-Sampling and Down-Conversion.

FIG. 4 shows A polyphase Partition of the Band Pass Filter Illustratingthe Factoring to-the-Right of Phase Rotators from the InitialUp-Conversion Heterodyne of the Filter Weights.

FIG. 5 shows Polyphase partition of a Single Prototype Low-pass Filter,With Post Filtering Phase Rotators Performing the Band Centering ComplexHeterodyne for Each Desired Output Center Frequency.

FIG. 6 shows Re-Sampled Polyphase Partition of the Band Pass Filter WithInput Commutator, Down Sampled Stages, FFT Based Post Filter PhaseRotators For Channels Selection, and Residual Frequency Shift of AliasedCenter Frequencies.

FIG. 7 shows Parallel Spectral Partition.

FIG. 8 shows Cascade Spectral Partition.

FIG. 9 shows Input-Output Signal Rates for Wideband Channelizer.

FIG. 10 shows Frequency Centers and Span for Six-Channel Channelizer.

FIG. 11 shows Fundamental processing blocks of a resampling six-channelchannelizer.

FIG. 12 shows Six stage resampling polyphase filter.

FIG. 13 shows Partition of Prototype Low Pass Weight Set for Use in anEmbedded 1-to-2 Down Sampling, Six Stage Polyphase Filter.

FIG. 14 shows Scheduling of Input data Commutator and Internal WeightSet Commutator.

FIG. 15 shows Input-Output Sample Rates of Narrow Band Channelizer.

FIG. 16 shows Cascade of Resampling 6-Channel and Resampling 5-ChannelChannelizers.

FIG. 17 shows Fundamental Processing Blocks of Narrowband Five-ChannelChanelizer.

FIG. 18 shows Resampling up-2, down 5, 5 Stage Polyphase Filter.

FIG. 19 shows Partition of Prototype Low Pass Weight Set for Use in anEmbedded 1-to-2 Down Sampling, Five Stage Polyphase Filter.

FIG. 20 shows Scheduling of Input data Commutator and Internal WeightSet Commutator.

When describing the processing technique presented herein we will usesample rates selected to satisfy the timing consideration. The samplerate indicated in FIG. 1 has been selected to demonstrate the highcomputational efficiency available for timing recovery from the processdescribed herein.

The tasks and the associated modules that implement the functions in atraditional receiver are: (1) Spectral Translation, (2) BandwidthReduction, and (3) Output Sample Rate Selection. The SpectralTranslation is performed by a complex heterodyne that translates thecenter of the desired spectral band to base-band. The complex heterodynemultiplies the input data sequence by samples of a cosine wave and asine wave with frequency selected to match the center of the desiredband. The Bandwidth Reduction is performed by a digital filter thatprocesses the complex input data stream of the down-converted signal.The digital filter performs the required weighted sums to form thereduced bandwidth output data stream. The digital filter performs alow-pass filtering process that restricts the signal bandwidth to thatof the translated band, and consequently rejects the remaining spectralcomponents of the translated signal. The Output Sample Rate Selection isperformed by a complex digital filter known as an interpolator thataccept input data from the previously described low-pass filter at afixed input rate that satisfies the Nyquist Criterion, and computes fromthese samples a set of output samples at an output rate different fromthe input rate and selected to satisfy some signal conditioningconstraint in subsequent processing following this processing block.

SUMMARY OF THE INVENTION

The invention described here combines two or more of the processingtasks described above in a single filter, and further has the singlefilter perform the tasks for more than one center frequency signal. Thefilter structure is the well-known polyphase partition. In thisstructure a single filter is partitioned into M-parallel paths eachrepresenting a section of the prototype filter. The outputs of thesepaths are combined with fixed phase rotators to obtain separate timeseries from the multiple center frequency bands of interest. In thisparallel path structure, different center frequencies only affect theset of scalar phase rotators associated with each path. Thus thecombination of polyphase partition with their post filter phase rotatorspermits the single filter to operate at each of the filter bank centerfrequencies simultaneously.

FIG. 3 presents block diagrams of the sequence of transformations thatpreserve the desired signal-processing task while establishing thecondition that enable a single polyphase partition of the filter toprovide outputs signals, simultaneously, from different centerfrequencies. In the traditional receiver structure, shown in FIG. 3 a,the complex heterodyne down converts or translates the spectrum of theinput signal from its center frequency to the center frequency of thelow-pass filter. Without loss of generality, we will assume the low passfilter is centered at DC or zero frequency.

In an equivalent, but alternate structure, a complex band pass filterreplaces the low pass filter. This filter has an impulse response formedas the product of the low pass impulse response h(n) and theup-converting complex heterodyne sequence exp(j 2 pi fc Ts n) of thesame length. Here the heterodyne is applied to the filter to move itscenter frequency to the band center of the signal rather than thestandard approach, which applies the heterodyne to the signal to moveits band to the filter's spectral location. In this structure, thefiltering occurs at the signal's center frequency, and the output of thefilter is properly band limited but still resides at the carrier centerfrequency. If it is desired to translate the signal spectra to baseband, this down conversion can be applied after the filter as shown inFIG. 3 b.

Since the signal bandwidth has been reduced by the band limiting actionof the digital filter, it is common to reduce the sample rate of thedown converted and filtered time series. The heterodyne following theband pass filter can be moved to the low data rate side of the downsampler. Now only the samples delivered to the output of the downsampler are subjected to the heterodyne and the workload of theheterodyne is reduced by the same M-to-1 ratio of the input to outputsampling rates. The down sampling operation is thus applied to theband-centered signal. Reducing the sample rate of the carrier centeredsignal results in an alias induced spectral translation of the centerfrequency from fc with angular rotation rate of 2 pi fc/fs per sample toan angular rotation rate of 2 pi M fc/fs modulo(2 pi). If the centerfrequency fc is any multiple of the output sample rate, say k fs/M, thenthe aliased rotation rate is 2 pi M (k fs/M)/fs modulo(2 pi) or k 2 pimodulo(2 pi) which is congruent to zero, which means the output rate ofrotation is zero radians per sample. For the proper choice of centerfrequency relative to sample rate, the down sampled data samplesrepresent a signal that has been aliased to DC. Selection of the samplerate to be an integer multiple of the signal center frequency is one ofthe suggested restrictions addressed earlier. The restriction is alsoapplicable when the ratio of sample rate to center frequency is arational ratio of small integers.

Any multiple of the output sample rate will alias to DC or zerofrequency. Similarly, any offset from a multiple of the output samplerate will alias to the same offset from DC or zero frequency. Aheterodyne following the down sampling can then remove this residualoffset. Thus the spectral translation from the channel center can beaccomplished at the filter output prior to the down sampling or afterthe down sampling by a combination of aliasing and reduced data rateheterodyne. The sliding of the output heterodyne to the downside of theoutput resampler is shown in FIG. 3 c. Applying the heterodyne after thedown sampling as opposed to prior to the down sampling results in areduction of computational workload for the heterodyne operation.

FIG. 4 presents the polyphase partition of the band pass filter, withthe filter operating at the input rate. In this M-fold partition thenumber of paths is defined by the number of center frequencies thatalias to zero frequency when the output time series of the filter isdown sampled from fs to fs/M. When the filtering operation includes theoption to down sample prior to the filter we are permitted to change theinput to output ratio by any rational ratio, 1/M representing only oneof the options.

FIG. 4 presents the partition of the prototype filter operating in thepartitioned mode at the input rate with the output heterodyne appliedafter the down sampling operation. Here the scalars that contributed tothe up-conversion heterodyne of the prototype low-pass filter have beenfactored forward and have been applied as scalar phase rotators aftereach sub filter. Different phase rotators with the same single filterpartition are associated with different center frequencies, thusmultiple center frequencies can be simultaneously accommodated withconcurrent sets of phase rotators. Thus the partitioned filter can beconsidered a single-input, multiple output process with the separateoutputs formed by phase-shifted sums of the sub filter outputs. Thisstructure is shown in FIG. 5.

When a large number of phase rotators are required to service multiplechannels, they are implemented as a fast Fourier transform (FFT). Westill have the option to perform the output heterodyne prior to downsampling, or after, and we still have the option to perform the downsampling, with an input commutator, prior to the filter segments ratherthan after. System considerations related to the interpolationrequirements following the filtering and down conversion influence wherethe down sampling operation is to be performed. Computational efficiencyis increased as the down sampler is moved towards the input data stream.Moving the down sampler to the input of the process results in thestructure shown in FIG. 6. The primary advantage of this structure isthat all of the processing, the partitioned filter, the phase rotators,and the residual heterodyne are accomplished at the output rate withnone of the processing proceeding at the input rate. This is the mostefficient multi-channel partition process.

One final consideration in this class of polyphase filter partitions isthat the down sampling that occurs via the input commutator can bemodified to permit M-to-P sample rate change as opposed to thetraditional M-to-1 change. This is accomplished by replacing the weightvector for each polyphase stage with a set of weight vectors that arecyclically accessed with period P while the stages are accessed withperiod M. This permits the sample rate change, normally allocated to asecond interpolation filter, to also be imbedded in the polyphasefilter. Thus the polyphase filter can, with proper attention toresampling, partitioning, and weight-set scheduling, accommodate thetranslation, filtering, and sample rate change of the entire filter bankprocess described in FIG. 2.

Returning to FIG. 1, we note that the signal spectra to be processed bythe receiver can have various mixes of narrow band and wide bandcomponents. This mix extends from zero, one, two, or three wide bandcomponents with eleven, eight, three, and zero narrowband componentsrespectively. At one end we have three wide band signals and at theother end we have eleven narrow band signals. The assets required forthese two extremes are different and can be optimized individually foreach signal set. The remaining two signal configurations are mixed andrequire assets for both low and high bandwidth processing.

Because of the two classes of signals to be processed, the polyphasefilter structure can be implemented as a cascade of processing tasks intwo modes. In the first mode, the filter is implemented as twoindependent parallel structures with one performing the processingrequired to implement or service the needs of all three wideband signalsand one performing the processing required to implement or service theneeds of the eleven narrowband signals. In the second mode, the filtersoperate in cascade with one filter partitioning the full input bandwidthinto overlapping spectral bands matched to the spectral width of thethree wideband components and one filter processing the reducedbandwidth signals obtained from the first filter to obtain, if required,additional bandwidth reduction matched to the narrowband signals. Theseconfigurations are shown in FIGS. 7 and 8. In both cases, processingassets not required to process the particular input signal configurationare disengaged and powered down. Following the philosophy that a filtershould operate at the lowest possible sample rate consistent with itsNyquist rate, we will emphasize the second option composed of cascadeprocessing tasks interspersed with appropriate resamplers betweenbandwidth reducing stages.

DESCRIPTION OF INVENTION

A set of digital filters composed of polyphase partitions of prototypelow pass filters coupled with a process for performing sample ratechanges within the filtering process is applied to the task ofperforming the simultaneous functions of channelizing, of filtering, andof resampling a frequency division multiplexed communication signal. Inparticular, the signal is a third generation (3G) signal suite composedof mixes of wideband UTRA (3.84 MHz) and narrowband (1.2244 MHz)spectral components with bandwidths and center frequencies shown in FIG.1.

The collection of Multirate signal processing partitions and schedulingpresented here take advantage of signal bandwidths and signal centerfrequency locations and separations to enable a single processingfunction to simultaneously perform bandwidth control, spectraltranslation, and resampling for separate channels with similar andrelated spectral characteristics. The process afford great reduction inprocessing load required to demodulate the multiple channels comprisingthe 3-G signal set.

The channelization system is first described at a high level by acollection of interconnected functional processing blocks assigned toperform specific processing tasks. The signal processing performed by aparticular block may represent the entire processing required to extracta desired signal component from the composite signal, or it mayrepresent one of a sequence of signal processing functions required toextract the desired signal. In general, the processing is performed in ahierarchal cascade of high level processing blocks. These blocks can bedescribed by interconnections of lower level processing blocks that arecommon to many of the high level blocks. The filtering blocks aretraditionally non-recursive because of the general ease with which theprototype low pass filter can be decomposed into polyphase segments. Aparticular class of recursive filters that permit the polyphasepartition of its prototype low pass realization can also be used to formthe processing blocks.

The recursive structures often exhibit spectral responses thatoccasionally require post processing spectral clean-up filters. Theseclean-up filters are unique to the recursive implementations, andrepresent additional processing blocks not present in the non-recursiveimplementation. The incentive to use a recursive implementation for thefiltering blocks is the significant reduction in processing required fora given filtering task. The recursive polyphase filter can beimplemented with structures that offer linear phase response, a propertyrequired to preserve signal fidelity. The recursive polyphase filter canalso be implemented with non-uniform phase, with a marked reduction inprocessing workload. This option is viable when the receiver includes achannel equalizer that will attribute the filter phase distortion to thechannel and correct it while inverting the channel response. Thenon-linear phase recursive polyphase structure offers additionalflexibility in parameter selection for the cascade processing tasks.Implementations that mix and match from the three realization optionscan also offer design flexibility. This patent only describes thenon-recursive implementation. Related and connected patents describe therecursive only, and the mixed non-recursive and recursiveimplementations.

First Processing Block

The first processing block of this invention is shown in FIG. 9 Thisblock processes the signal composed of three wideband components, each3.84 MHz wide, and separated by 5-MHz spectral centers. This spectrum isthe first one shown in FIG. 1. The input sample rate is 15.36 MHz, afrequency selected so that the desired output sample rate of 6.144 MHzis easily available by a sample rate change of 2-to-5 (up 2 and down 5).The Spectral responses of the six-channel channelizer are shown in FIG.10. Three of the bands, centered at −fs/3, 0, and fs/3(−5.12 MHz, 0 MHz,and +5.12 MHz) are almost matched to the center frequency of thethree-wideband UTRA carriers. The bandwidth spanned by the equivalentfilters in the channelizer exceeds the UTRA bandwidth by a margin thatallows for the offset of center frequencies. The remaining three bandsoverlap the first three and are centered at −fs/6, fs/2, and −fs/3(−2.56 MHz, 7.68 MHz and −2.56 MHz). The band centered at the halfsample rate is discarded so that five bands are extracted from thechannelizer. The remaining pair of this second frequency set arereserved for sub-band partitioning of the CDMA-2000 carriers that areplaced at ±2.56 MHz slots in two of the frequency assignment plans (seeFIG. 1, third and fourth options).

Three fundamental processing blocks shown in FIG. 11 forms theresampling six-channel Channelizer.

The initial processing block of the resampling 6-channel Channelizer isa resampling six-stage polyphase filter (P-210) that is shown in FIG.12. The output of the polyphase filter is processed by a 6-point DFT(P-220) that may be implemented directly as a DFT or as a 6-point FFT.The 6-point DFT contains and applies the phase rotators to the output ofthe polyphase filter to perform a phase coherent extraction of thedesired Nyquist zone from the aliased components now residing at zerofrequency due to the down sampling operation. Heterodynes (P-230) areapplied to four of the channelized time series to remove a residualfrequency offset of the spectra aliased from the Nyquist zones centeredat +5.12 MHz, 2.56 MHz, −2.56 MHz and −5.12 MHz. The residual offsets of0.12 and of 0.06 MHz are the 0.12 MHz and 0.06 MHz offsets from thealiased center frequency relative to the channel center frequencies of±5.00 MHz and ±2.56 MHz respectively.

The resampling six-stage polyphase filter (P-210) shown in FIG. 12, isformed as a multi-path filter containing six stages (P-210A, P-210B,P-210C, P-10D, P-210E, and P-210F) and commutator (P-212) as a means fordelivering successive samples of the input data stream to appropriatesstages of the polyphase filter. A control mechanism, not shown,schedules input samples to successive stages while simultaneouslyscheduling weight sets to those stages. The interaction of the twoscheduling routines accommodates a simultaneous 1-to-2 up sampling ofthe input data stream and a 5-to-1 down sampling of each output stream.The polyphase partition of a prototype low pass filter with designbandwidth matched to signal bandwidth (3.84 MHz+0.24 MHz), but designedwith double sample rate (30.72 MHz) to accommodate the embedded 1-to-2up sampling is shown in FIG. 13. As indicated, the partition for ther-th stage is hr(n)=h(r+6n).

The scheduling of the input commutator and of the weights of thispolyphase partition is shown in FIG. 14. Here the six registers storingthe input samples are labeled from top to bottom Reg_A, Reg_B, Reg_C,Reg_D. Reg_E, and Reg_F respectively. A state machine that cyclesthrough twelve consecutive state conditions for FIG. 14 controls thecommutator scheduling. This schedule is shown in table 1. The way thetable is to read is as follows. In state 1. Three inputs are deliveredin order to upper-case registers C, B, and A. In this state, lower-caseregisters f, e, and d receive no inputs. Filter weights 5, 3, 11, 9, and7 are applied to the data in the registers which have the same orderingas the registers. That is, in this state, Register C receives inputsample d(n) and applies Weight Set 5, Register B receives input sampled(n+1) and applies Weight Set 3, Register A receives input sample d(n+2)and applies Weight Set 1. No additional inputs are received in thisstate. The remaining registers apply the indicated Weights Sets to theircontents without having received new input samples as indicated:Register f applies Weight Set 11, Register e applies Weight Set 9, andregister d applies Weight Set 7. Note that in successive states, theinput port distributes either 3 or 2 samples to the appropriateregisters, and that the weight sets alternate between the even indexedand the odd indexed assignments.

-   state #1 3-inputs C,B,A,f,e,d filters 5,3, 1,11,9,7-   state #2 2-inputs F,E,d,c,b,a filters 4,2,12,10,8,6-   state #3 3-inputs D,C,B,a,f,e filters 5,3, 1,11,9,7-   state #4 2-inputs A,F,e,d,c,b filters 4,2,12,10,8,6-   state #5 3-inputs E,D,C,b,a,f filters 5,3, 1,11,9,7-   state #6 2-inputs B,A,f,e,d,c filters 4,2,12,10,8,6-   state #7 3-inputs F,E,D,c,b,a filters 5,3, 1,11,9,7-   state #8 2-inputs C,B,a,f,e,d filters 4,2,12,10,8,6-   state #9 3-inputs A,F,E,d,c,b filters 5,3, 1,11,9,7-   state #10 2-inputs D,C,b,a,f,e filters 4,2,12,10,8,6-   state #11 3-inputs B,A,F,e,d,c filters 5,3, 1,11,9,7-   state #12 2-inputs E,D,c,b,a,f filters 4,2,12,10,8,6

Table 1. State Related to Input Port Commutator and Internal WeightVector Commutators

The schedule of FIG. 14 allows for alternate processing of three inputsamples and then two input samples so that for every five inputs weextract two outputs from each polyphase output port. The interaction ofthe input commutator (P-214) and the weight commutators (P_216) reflectsthe book keeping involved in tracking the non zero samples of anequivalent 1-to-2 zero-packing for the 1-to-2 up sampling at the filterinput.

The six output samples from the output ports of the resampling 6-stagepolyphase filter are presented to a six-point DFT (P-220). This is astandard numerical algorithm that can be implemented directly as apruned collection of Inner-products, as a factored FFT, or as a reducedmultiplication Winograd Transform.

The five retained output samples from the 6-point DFT are time samplesrepresenting translated, filtered, and re-sampled signals from each ofthe center frequency bands described earlier. These include thethree-wideband signals comprising the 3-G signal set as well as theoverlapped bands centered at ±2.5 MHz that are only used in the last twofrequency assignments shown in FIG. 1.

Note that a single stage prototype filter has been used to filter,translate, and resample all three wideband channels. As well as preparethe overlapped bands for further processing. The filter length selectedto demonstrate and verify concepts was of length 200, which whendistributed over the 12 polyphase stages mapped into 21 coefficients perstage. Let us compare the savings attributable to the polyphase filterpartition. In the direct implementation, a 90-tap prototype low pass FIRfilter will meet the transition bandwidth and out-of-band attenuationrequirements for the broadband channel decomposition. Similarly, a10-tap prototype low pass FIR filter will meet the transition bandwidthand out-of-band attenuation requirements of the up-2, down-5interpolator. Using these lengths as a benchmark, we can compare therelative workloads, in equivalent complex operations, of the twooptions, direct processing and the technique described here. A complexoperation (comp-op) is considered to be a complex scalar multiply andadd, requiring two real multiplies and adds. In the directimplementation, the workload to process 5 input samples is 20 comp-opsfor the input heterodynes, 1350 comp-ops for the three filters, and 60comp-ops for the interpolators. The workload for all three channels is1430 comp-ops per 5-inputs or equivalently 1430 comp-ops per 2-outputs.Normalizing by the number of channels and number of data points weobtain a workload of approximately 95 comp-ops per input data point perchannel or 238 comp-ops per output data point per channel. In thepolyphase resampling implementation the workload to process 5 inputsamples is 200 comp-ops for the filter, 16 comp-ops for the DFT, and 40comp-ops for the output heterodynes for a total of 256 comp-ops per5-inputs or 256 comp-ops per 2-outputs. Normalizing by number ofchannels and number of data points we obtain a workload of approximately17 comp-ops per input data point per channel or 44 comp-ops per outputdata point per channel. The relative workload for the direct versus thepolyphase resampler is approximately 5-to-1. In this comparison, weincluded the complex heterodynes and DFT processing required for the twooverlapped channels an unnecessary processing burden for the threewide-band channels.

Second Processing Block

We now consider the second processing block of this invention, theresampling 5-channel channelizer that is shown in FIG. 15. Thisprocessing block performs the second level partition of the widebandbandwidth into three narrowband bands occupying the same nominalbandwidth of the single broadband channel. This process also extractsthe narrowband signal from the two overlapped bands when required. Thisset of signals is composed of three or four CDMA-2000 channels separatedby 1.25 MHz offsets and centered at +5.0 MHz as shown in the mixedsignal set presented in the second option in FIG. 1.

The 5-channel resampling channelizer uses the 6-channel resamplingchannelizer as a preprocessor and initial bandwidth and sample ratereducer. This arrangement is shown in FIG. 16.

Three fundamental processing blocks of the resampling 5-channelchannelizer are shown in FIG. 17.

The initial processing block of the narrowband 3-channel Channelizer isa resampling five-stage polyphase fiter (P-410) that is shown in FIG.18. The output of the polyphase filter is processed by a 5-point DFT(P-420) that may be implemented directly as a pruned DFT or as a 5-pointWinograd FFT. The 5-point DFT contains and applies the phase rotators tothe output of the polyphase filter to perform a phase coherentextraction of the desired Nyquist zones from the aliased components nowresiding at zero frequency due to the down sampling operation.Heterodynes (P-430) are applied to three of the channelized time seriesto remove a residual frequency offset of the spectra aliased from thetwo Nyquist zones centered at +1.2288 MHz and −1.2288 MHz and theNyquist zone at 2.4576 MHz. The residual 0.0212 MHz and 0.0424 MHzoffsets are the 0.0212 MHz offset and 0.0424 MHz offset from the aliasedcenter frequency of the channel center frequencies of +1.250 MHz and2.500 MHz.

The resampling five-stage polyphase filter (P-410) shown in FIG. 18, isformed as a multi-path filter containing five stages (P-410A, P-410B,P-410, P-410D, and P-410E) and commutator (P-416) as a means fordelivering successive samples of the input data stream to appropriatestages of the polyphase filter. A control mechanism, not shown,schedules input samples to successive stages while simultaneouslyscheduling weight sets to those stages. The interaction of the twoscheduling routines accommodates a simultaneous 1-to-2 up sampling ofthe input data stream and a 5-to-1 down sampling of each output stream.

Here the polyphase filter is applied to the signal to affect thespectral aliasing and apply a course bandwidth reduction to permit asample rate reduction to 2-samples per symbol. The polyphase partitionof a prototype low pass filter with design bandwidth matched to signalbandwidth (1.2288 MHz) but with large transition band (1.2288 MHZ) anddesigned with double sample rate (12.288 MHz) to accommodate theembedded 1-to-2 up sampling is shown in FIG. 19. As can be seen, thepartition for the r-th stage is hr(n)=h(r+10n).

The scheduling of the input commutator and of the weights of thispolyphase partition is shown in FIG. 20. Here the five registers storingthe input samples are labeled from top to bottom Reg_A, Reg_B, Reg_C,Reg_D, and Reg_E respectively. The input data samples are introduced tosuccessive input ports as the commutator moves cyclically up portaddresses. A state machine that cycles through two consecutive stateconditions listed in FIG. 20 controls the commutator scheduling. Theschedule allows for alternate scheduling of three input sample and thentwo input samples so that for every five inputs we extract two outputsfrom each polyphase output port. The interaction of the input commutator(P-414) and the weight commutators (P_416) reflects the book keepinginvolved in tracking the non zero samples of an equivalent 1-to-2zero-packing for the 1-to-2 up sampling at the filter input.

The scheduling process coupling the input commutator and the internalweight commutatotrs is shown in table 2.

-   State #1 3-inputs: C,B,A,f,e Filters: 3,2,1,5,4-   State #2 2-inputs: F,E,c,b,a Filters: 2,1,5,4,3    Table 2: State Schedule for Commutating Input Samples to Internal    Registers and for mmutating Filter Weight Sets to Internal Registers    -   The five output samples from the output ports of the resampling        5-stage polyphase filter are presented to a five-point DFT        (P-420) from which we extract three or four of the five outputs.        This is a standard numerical algorithm that can compute the 4 or        5 desired output points as a pruned collection of inner        products, or as a Winograd Transform requiring fewer products.        The three or four output samples from the 5-point DFT are time        samples representing translated, filtered, and re-sampled        signals from each of the narrowband signals comprising the        CDMA-2000 signal set. As described earlier, the aliased signals        from the ±1.250 MHz and 2.50 MHz centers are further heterodyned        by the pair of complex heterodynes (P-430) to finish the        translation process.

Note that a single stage prototype filter has been used to filter,translate, and resample all three or four narrowband channels from aninitial input rate of 5 samples per symbol down to a lower sample rateof 2 samples per symbol. A 108-tap prototype low pass FIR filter willmeet the transition bandwidth and out-of-band attenuation requirements.Using this length as a benchmark, we can compare the relative workloads,in equivalent complex operations, of the two options, direct processingand the technique described here. In the direct implementation, theworkload to process each input sample is 2 comp-ops for the inputheterodyne and 40 comp-ops for the filter for a total of 104 comp-opsper input per channel. In the polyphase resampling implementation usingthe same filter, the workload to process 5 input samples is 80 comp-opsfor the filter, 16 comp-ops for the DFT, and 12 comp-ops for the outputheterodynes This is a total of 108 comp-ops per 5-inputs. Normalizing bythe number of channels and number of input data points we obtain aworkload of approximately 5 comp-ops per input data point per channel.The workload ratio for direct versus the down sampling technique isapproximately 21-to-1. The embodiment of the invention currentlypreferred by the inventor has been described, but one skilled in the artof digital signal processing and digital receiver design will be enabledby acquaintance with the foregoing disclosure to design a number ofalternative embodiments of this invention, and this should be borne inmind when construing the scope of the claims which follows thisspecification.

1. A receiver for receiving and efficiently separating a composite 3-Gwireless communications signal into constituent baseband components,wherein said receiver combines multiple processing tasks of a 3-Greceiver into a single device, said device performs the processingrequired for multiple channels, the single device comprising, aresampling polyphase filter for performing tasks of simultaneousspectral translation of multiple contiguous spectral regions tobaseband, the tasks including: a.) separating the signals residing inthe multiple contiguous spectral regions for bandwidth reduction of eachof a varied bandwidth signal component, b.) performing interpolation tochange sample rates of each of a multiple output series by a rationalratio matched to the bandwidth of each signal component, and a singlepolyphase filter coupled to operate in a resampling mode such thatsample rate inputs and sample rate outputs are different.
 2. A receiverfor receiving and efficiently separating a composite 3-G wirelesscommunications signal into constituent baseband components, wherein saidreceiver combines multiple processing tasks of a 3-G receiver into asingle device, said device performs the processing required for multiplechannels, the single device comprising, a filter for; a.) changing asample rate to induce spectral aliasing of multiple spectral regions,and b.) operating in a resampling mode for intentional aliasing of eachof several spectral regions and outputting simultaneous separate datastreams from varied bandwith spectral regions at varied output samplerates.